In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Danilo Poccia discusses NoSQL technology. Includes an introduction to NoSQL DB and a discussion of when it is time to consider NoSQL. Danilo also introduces Amazon DynamoDB as a NoSQL solution and talks through several case studies of customers that are using Amazon DynamoDB today.

1. How and When to Use
NoSQL DBs
Danilo Poccia | Technical Evangelist
danilop@amazon.com
@danilop

2. We will talk about
• What is NoSQL DB
• When it is time to consider NoSQL
• Amazon DynamoDB as an NoSQL solution
• Case studies

3. What is a “Database”?
• Data Persistence
• Data Model
• Data Retrieval

4. Traditional RDBMS vs NoSQL
RDBMS NoSQL
Data Model
Data Retrieval

5. Traditional RDBMS vs NoSQL
RDBMS NoSQL
Data Model Relational
Data Retrieval SQL

6. Traditional RDBMS vs NoSQL
RDBMS NoSQL
Data Model Relational Not Relational
Data Retrieval SQL Not SQL

7. Relational Databases
Scale
Database Query Performance
Desired
consistency,
predictability

8. Relational Databases
Scale
Database Query Performance
Desired
consistency,
predictability
Actual
degraded
performance
with
scale

9. Scale
Database Query Performance
Desired
consistency,
predictability
Actual
degraded
performance
with
scale
Management problems
Data
sharding
Data
caching
Provisioning
Cluster
management
Fault
management
Relational Databases

10. NoSQL DB typical features
• Non-relational
• Distributed
• Eventually consistent
• Horizontally scalable
• Support replication
• Schema-free

11. Typical use cases for NoSQL
• Fast reads/writes with very low jitter
• Huge amounts of data

12. NoSQL on AWS

13. NoSQL on AWS
• Deploy popular third-party solutions via EC2
– MongoDB
– Cassandra
– Redis

14. NoSQL on AWS
• Deploy popular third-party solutions via EC2
– MongoDB
– Cassandra
– Redis
OR
• Use a managed AWS service – Amazon DynamoDB

15. Tools Positioning Matrix
S3
Glacier
Redshift
Elastic MapReduce
RDS
Large
Size
Small
Dynamo
DB
Elasti
Cache
Low Latency / Complexity High

16. Amazon DynamoDB

17. Amazon DynamoDB
NoSQL Database
Fast & predictable performance
Seamless Scalability
Easy administration
“Even though we have years of experience with large, complex NoSQL
architectures, we are happy to be finally out of the business of managing it
ourselves.” - Don MacAskill, CEO
ADMIN

18. Access and Query Model
Two primary key options
§ Hash key: Key lookups: “Give me the status for user foo”
§ Composite key (Hash with Range): “Give me all the status updates for user ‘foo’
that occurred within the past 24 hours”
Support for multiple data types
§ Scalar: number, string, binary
§ Multi-valued: number set, string set, binary set
Consistency: Supports both strong and eventual consistency
§ Pick consistency mode at per API call
§ Different parts of applications can make different choices

19. Operations
Table Operations
§ CreateTable,
UpdateTable,
DeleteTable
§ ListTables,
DescribeTable
Item Operations
§ GetItem,
BatchGetItem
§ PutItem,
UpdateItem,
DeleteItem,
BatchWriteItem
Query & Scan
§ Query,
Scan
Atomic Counters and Conditional updates

20. Social Network
hash + range schemas

21. Social Network
• Store info about users
• Query for a user’s friends

22. Social Network
Friends Table Users Table

23. User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01
Social Network
Users Table

24. User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01
Social Network
Users Table
Item

25. User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01
Social Network
Users Table
Attribute
(string, number, binary, set)

26. User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01
Social Network
Users Table
Primary Key
(Hash)

27. User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01
Social Network
Friends Table
User Friend
Bob Alice
Alice Bob
Alice Carol
Alice Dan
Users Table

28. Social Network
Friends Table
User Friend
Bob Alice
Alice Bob
Alice Carol
Alice Dan
Users Table
Hash-and-Range
Primary Key Schema User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01

29. Social Network
Friends Table
User Friend
Bob Alice
Alice Bob
Alice Carol
Alice Dan
Query for Alice’s friends
Users Table
User Birthday
Bob 11.02
Alice 15.10
Carol 30.06
Dan 05.01

30. DynamoDB Indexes
Local Secondary Index (LSI)
- Same Hash Key as Primary Key
- Different Range Key
Global Secondary Index (GSI)
- New Hash and Range Key
- Eventually Consistent

31. DynamoDB Highlights: Performance
Typical service-side latency: single digit milliseconds
Solid State Drive (SSD)-backed service
Latency is consistent
– As throughput increases
– As storage grows
No need for tuning.

32. DynamoDB Highlights: Reliability
Durability
– Synchronous replication for high durability
– A write is only acknowledged (committed) once it exists in at least two
physical data centers
– All writes occur to disk, not memory
Availability
– Regional service
– Spans multiple
Availability Zones (AZ)
– All data is continuously
replicated to multiple AZ’s

33. Provisioned Throughput
Reserve the throughput needed for each table
– Set at table creation
– Example: My table needs 1,000 writes/second and
5,000 reads/seconds of capacity
Increase / decrease via API call
Pay for throughput and storage (not instances)

34. Provisioned Throughput
Why?
– Simpler capacity planning
– Easy to translate calls to Apps => calls to database
– Not in terms of servers and disk IOPS
– Do not be locked in your peak
for month or year!

35. Capacity we needed before DynamoDB
Actual traffic
Capacity we can provision
with DynamoDB

36. DynamoDB Customer Highlights
x

37. Amazon DynamoDB Demo
Quick look at the Console
Sample use case
Geohash indexed by a GSI

38. How and When to Use
NoSQL DBs
Danilo Poccia | Technical Evangelist
danilop@amazon.com
@danilop